The present invention relates to a distance sensor for a vehicle having a sensor for transmitting microwaves or light, or for receiving an echo signal reflected by a target object.
In the case of speed regulators having a distance sensor (Adaptive Cruise Control, ACC) adapting travel speed of a motor vehicle to slower vehicles traveling ahead, when these are detected by the distance sensor, is already known. However, the distance sensor has a limited detection range, and thus can only detect such vehicles as are located in the prospective course range of the following vehicle. A misalignment of this detection range, which can occur either during installation on the vehicle or during operation, has the effect, however, that the longitudinal axis of the distance sensor relatively to the nominal alignment (center line of the vehicle) has a systematic angle of deviation. This can have the result that this misalignment, for example, leads to a faulty lane assignment of a detected radar object on the path of motion of the motor vehicle (trajectory), that is, to a vehicle being followed or coming in the opposite direction, and that thereby an undesired reaction of the speed regulator can take place.
A compensating device is known, for example, from German Published Patent Application No. 197 46 524, for compensating for the installation tolerances of a distance sensor in a vehicle, in which the installation tolerances of a distance sensor are compensated. Using an electronic evaluation device, current object distances and a current object angle are measured during travel, for detected objects relatively to the vehicle axis. In this connection, the misalignment angle to the current target object is determined by forming an average value of many measurements. It is true, though, that this average value formation functions satisfactorily only if the vehicle can follow the target object, a second vehicle traveling ahead, on a sufficiently long straight path, so that frequent measurements to the target object can be carried out. In the case of curves in the road or, also, uphill and down dale travel with changing angle of altitude, this method fails.
On the other hand, in the case of the device for calculating and correcting a misalignment angle for a distance sensor according to European Published Patent Application No. 0 782 008 the angle of deviation from the center line is described, using a regression method. To do this, the angle is measured in each measurement cycle as a function of the distance from moving, or better still, from fixed radar objects. In particular in dense traffic, however, there are not enough suitable objects within sight range of the sensor, so that not enough measured values are available. Thus, each method has the disadvantage that the availability of measured values depends on the travel situation or the traffic situation, as the case may be.
By comparison, the distance sensor or the speed regulator according to the present invention has the advantage that the reliability of the misalignment identification increases by the combination of a plurality of methods for determining a misalignment angle.
A particular advantage as compared to the known related art is considered also to be that the measurements for the misalignment angle can be carried out, not only on a straight travel path, but also along a curve. More measured values result from this, which, in particular, also favor the formation of the average value.
It is especially advantageous that a yaw rate sensor is provided as a further instrument, whose signals can be used for correcting trajectory curves. Since the yaw rate sensor detects the rotary motion of the vehicle about the vertical axis, it thereby also detects, in consideration of the driving speed, the bend in the travel path, or the curve, so that, from these data, appropriate angle calculations with respect to a vehicle driving ahead, which has been detected by the sensor, can be carried out The bend of a trajectory, in this connection, is looked upon as being the reciprocal value of the radius of the path, (in English: the curvature).
With the aid of adaptive long-term filtering, quality indicators of the trajectory are ascertained from the ascertained misalignment angles of individual trajectories. With the aid of the quality indicators of the trajectory, reliability of the angle measurement is advantageously improved. In this case, for example, the determination of the quality indicators is made from the correlation value of a regression analysis of the curvature, the number of measured values, the length of the trajectory and/or the speed of the object. Since these parameters are relatively simple to measure, this also makes possible a simple calculation of the quality indicator.
For the application of adaptive long-term filtering of the ascertained misalignment angle from individual trajectories, for example, a noise-optimized, linear, adaptive filter (e.g. a Kalman filter) is suitable, or a nonlinear filter in which the weighting of the individual measured values from the quality valuation is based on the quality indicators of the trajectory.
A nonlinear filter can also be used as a suitable adaptive long-term filter, in which the weighting of the individual measured values is done from the quality appraisal.
It is regarded as a special advantage that, with a positioning of the sensor outside the center line of the motor vehicle, the control system ascertains the misalignment angle with respect to the center line of the motor vehicle. That also causes the lateral angle arising from the center displacement of the sensor to be compensated for.
It is also favorable that the ascertainment of the misalignment angle is weighted either as a function of the weighted average values of the yaw rate sensor or of the displacement from the center line. This yields an improvement in the signal quality, which improves the robustness of the method for determining the misalignment angle, depending on the availability of the individual systems, since almost always at least one of the two methods receives suitable input data. Thereby one method advantageously compensates for the weaknesses of the other method.
By weighting the averaged mean values of the two individual methods, one obtains an improved signal quality.